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首页> 外文会议>International conference on graphic and image processing >Using Infrared HOG-based Pedestrian Detection for Outdoor Autonomous Searching UAV with Embedded System
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Using Infrared HOG-based Pedestrian Detection for Outdoor Autonomous Searching UAV with Embedded System

机译：基于红外HOG的行人检测技术在嵌入式系统户外自主搜索无人机中的应用

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Pedestrian detection (PD) is an important application domain in computer vision and pattern recognition. Unmanned Aerial Vehicles (UAVs) have become a major field of research in recent years. In this paper, an algorithm for a robust pedestrian detection method based on the combination of the infrared HOG (IR-HOG) feature and SVM is proposed for highly complex outdoor scenarios on the basis of airborne IR image sequences from UAV. The basic flow of our application operation is as follows. Firstly, the thermal infrared imager (TAU2-336), which was installed on our Outdoor Autonomous Searching (OAS) UAV, is used for taking pictures of the designated outdoor area. Secondly, image sequences collecting and processing were accomplished by using high-performance embedded system with Samsung ODROID-XU4 and Ubuntu as the core and operating system respectively, and IR-HOG features were extracted. Finally, the SVM is used to train the pedestrian classifier. Experiment show that, our method shows promising results under complex conditions including strong noise corruption, partial occlusion etc.
机译：行人检测（PD）是计算机视觉和模式识别中的重要应用领域。近年来，无人机已经成为研究的主要领域。本文基于无人机的机载红外图像序列，针对高度复杂的室外场景，提出了一种结合红外HOG（IR-HOG）特征和SVM的鲁棒行人检测算法。我们的应用程序操作的基本流程如下。首先，安装在我们的室外自主搜索（OAS）无人机上的红外热像仪（TAU2-336）用于拍摄指定的室外区域。其次，使用高性能嵌入式系统分别以三星ODROID-XU4和Ubuntu为核心和操作系统完成图像序列的采集和处理，并提取IR-HOG特征。最后，SVM用于训练行人分类器。实验表明，我们的方法在复杂的条件下（包括强噪声破坏，部分遮挡等）显示出令人鼓舞的结果。

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